Best for
Long-running agent systems that need better memory structure than plain notes or scattered files.
Ontology
Typed knowledge graph memory for agents
productivity openclawclawhub
91,000 downloads
224 stars
Editor signal: Featured by editorial review
Source confidence: High
Provides typed knowledge-graph memory with entity queries, composable capability modeling, and multi-step planning support.
What it does
Provides typed knowledge-graph memory with entity queries, composable capability modeling, and multi-step planning support.
Why it matters
Provides typed knowledge-graph memory with entity queries, composable capability modeling, and multi-step planning support.
Platform fit
Best aligned with openclaw, clawhub workflows, with category focus on productivity.
Not ideal for
Very short-lived tasks where durable memory and typed entities add more setup than value.
Common use cases
- Track entities, relationships, and evolving knowledge across repeated sessions.
- Support multi-step planning with reusable memory structures.
- Provide a stable memory backbone for long-running autonomous workflows.
Installation notes
Begin with a narrow set of core entities and relationships, then expand the memory schema only after repeated workflows prove it useful.